The problem discussed here is one of scheduling the tasks in identical parallel machines. In this problem, we deal with a set of n tasks and m identical parallel machines, with the objective of minimizing the makespan. The makespan is the total processing time of the most busy machine. This work presents an implementation of a memetic-neuro scheduler for solving this scheduling problem. The memetic algorithm, which is an hybrid version of genetic algorithm with local search, has been used to evolve good scheduling forms; and the neural network has been used to calculate the fitness for each individual of the population.